Josh Lewis is the VP, Product at Alpine Data. Josh has ten years of experience across academia and industry in machine learning, data analysis, cognitive science and user experience. Prior to joining Alpine, Josh lead the frontend engineering team at Ayasdi where he built apps and APIs for the healthcare, pharmaceutical and finance verticals, as well as Ayasdi’s domain-general data analysis and visualization software.
Before joining Ayasdi, Josh was a PhD student and postdoc at the UC San Diego Cognitive Science Department where he investigated the role of human perception and insight in the data analysis process. He also developed novel software for applying unsupervised machine learning algorithms called Divvy, a project that was supported by a multi-year NSF grant.
Josh graduated from Pomona College with majors in Cognitive Science and Philosophy.
The opinions expressed in this blog are those of Josh Lewis and do not necessarily represent those of IDG Communications, Inc., its parent, subsidiary or affiliated companies.
Hadoop provides power and versatility for data scientists, at the cost of complexity.
The future has fewer jobs, but those that remain will be better.
A failed standard, complex alternatives -- and a way forward.
Discovering and targeting micropopulations for politics and profit
Hype aside, deep learning can open up new sources of data for business analysis
The time-tested technique for predicting numbers, and the role of domain knowledge in machine learning.
When the cost of an error isn’t trivial, we need better approaches to error mitigation to operationalize and scale machine learning
As a businessperson, the ability to make specific, actionable requests of your data scientists, hold them to a high standard and connect their work to relevant action is basic contemporary corporate literacy.